Machine vision lights as important as sensors and optics

Lighting matters as much or more than camera (sensor) selection and optics (lensing). A sensor and lens that are “good enough”, when used with good lighting, are often all one needs. Conversely, a superior sensor and lens, with poor lighting, can underperform. Read further for clear examples why machine vision lights are as important as sensors and optics!

Assorted white and color LED lights – courtesy of Advanced Illumination

Why is lighting so important? Contrast is essential for human vision and machine vision alike. Nighttime hiking isn’t very popular – for a reason – it’s not safe and it’s no fun if one can’t see rocks, roots, or vistas. In machine vision, for the software to interpret the image, one first has to obtain a good image. And a good image is one with maximum contrast – such that photons corresponding to real-world coordinates are saturated, not-saturated, or “in between”, with the best spread of intensity achievable.

Only with contrast can one detect edges, identify features, and effectively interpret an image. Choosing a camera with a good sensor is important. So is an appropriately matched lens. But just as important is good lighting, well-aligned – to set up your application for success.

What’s the best light source? Unless you can count on the sun or ambient lighting, or have no other option, one may choose from various potential types of light:

  • Fluorescent
  • Quartz Halogen – Fiber Optics
  • LED – Light Emitting Diode
  • Metal Halide (Mercury)
  • Xenon (Strobe)
Courtesy of Advanced Illumination

By far the most popular light source is LED, as it is affordable, available in diverse wavelengths and shapes (bar lights, ring lights, etc.), stable, long-life, and checks most of the key boxes.

The other light types each have their place, but those places are more specialized. For comprehensive treatment of the topics summarized here, see “A Practical Guide to Machine Vision Lighting” in our Knowledgebase, courtesy of Advanced Illumination.

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Download whitepaper

Lighting geometry and techniques: There’s a tendency among newcomers to machine vision lighting to underestimate lighting design for an application. Buying an LED and lighting up the target may fill up sensor pixel wells, but not all images are equally useful. Consider images (b) and (c) below – the bar code in (c) shows high contrast between the black bars and the white field. Image (b) is somewhere between unusable or marginally usable, with reflection obscuring portions of the target, and portions of the (should be) white field appearing more grey than white.

Courtesy of Advanced Illumination

As shown in diagram (a) of Figure 22 above, understanding bright field vs dark field concepts, as well as the specular qualities of the surface being imaged, can lead to radically different outcomes. A little bit of lighting theory – together with some experimentation and tuning, is well worth the effort.

Now for a more complex example – below we could characterize images (a), (b), (c) and (d) as poor, marginal, good, and superior, respectively. Component cost is invariant, but the outcomes are sure different!

Courtesy of Advanced Illumination

To learn more, download the whitepaper or call us at (978) 474-0044.

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Color light – above we showed monochrome examples – black and white… and grey levels in between. Many machine vision applications are in fact best addressed in the monochrome space, with no benefit from using color. But understanding what surfaces will reflect or absorb certain wavelengths is crucial to optimizing outcomes – regardless of whether working in monochrome, color, infrared (IR), or ultraviolet (UV).

Beating the same drum throughout, it’s about maximizing contrast. Consider the color wheel shown below. The most contrast is generated by taking advantage of opposing colors on the wheel. For example, green light best suppresses red reflection.

Courtesy of Advanced Illumination

On can use actual color light sources, or white light together with well-chosen wavelength “pass” or “block” filters. This is nicely illustrated in Fig. 36 below. Take a moment to correlate the configurations used for each of images (a) – (f), relative to the color wheel above. Depending on one’s application goals, sometimes there are several possible combinations of sensor, lighting, and filters to achieve the desired result.

Courtesy of Advanced Illumination

Filters – can help. Consider images (a) and (b) in Fig. 63 below. The same plastic 6-pack holder shown is shown in both images, but only the image in figure (b) reveals stress fields that, were the product to be shipped, might cause dropped product, reduced consumer confidence in one’s brand. By designing in polarizing filters, this can be the basis for a value-added application, automating quality control in a way that might not have been otherwise achievable – or not at such a low cost.

Courtesy of Advanced Illumination

For more comprehensive treatment of filter applications, see either or both Knowledgebase documents:

Powering the lights – should the be voltage-driven or current-driven? How are LEDs powered? When to strobe vs running in continuous modes? How to integrate light controller with the camera and software. These are all worth understanding – or having someone in your team – whether in-house or a trusted partner – who does.

For comprehensive treatment of the topics summarized here, see Advanced Illumination’s “A Practical Guide to Machine Vision Lighting” in our Knowledgebase:

Download whitepaper
Download whitepaper

This blog is intended to whet the appetite for interest in lighting – but it only skims the surface. Machine vision lights as important as sensors and optics. Please download the guide linked just above – to deepen your knowledge. Or if you want help with a specific application, you may draw on the experience of our sales engineers and trusted partners.

1st Vision’s sales engineers have over 100 years of combined experience to assist in your camera and components selection.  With a large portfolio of lensescablesNIC card and industrial computers, we can provide a full vision solution!

Effilux LED bar lights for machine vision – adjustable and modular!

Various LED bar configurations

Effective machine vision outcomes depend upon getting a good image. A well-chosen sensor and camera are a good start. So is a suitable lens. Just as important is lighting, since one needs photons coming from the object being imaged to pass through the lens and generate charges in the sensor, in order to create the digital image one can then process in software. Elsewhere we cover the full range of components to consider, but here we’ll focus on lighting.

While some applications are sufficiently well-lit without augmentation, many machine vision solutions are only achieved by using lighting matched to the sensor, lens, and object being imaged. This may be white light – which comes in various “temperatures”; but may also be red, blue, ultra-violet (UV), infra-red (IR), or hyper-spectral, for example.

LED bar lights are a particularly common choice, able to provide bright field or dark field illumination, according to how they are deployed. The illustrations below show several different scenarios.

Example uses of LED bar lights

LED light bars conventionally had to be factory assembled for specific customer requirements, and could not be re-configured in the field. The EFFI-Flex LED bar breaks free from many of those constraints. Available in various lengths, many features can be field-adapted by the user, including, for example:

  • Color of light emitted
  • Emitting angle
  • Optional polarizer
  • Built-in controller – continuous vs. strobed option
  • Diffuser window opacity: Transparent, Semi-diffusive, Opaline
EFFI-Flex user-configurable LED bar
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While the EFFI-Flex offers maximum configurability, sister products like the EFFI-Flex-CPT and EFFI-Flex-IP69K offer IP67 and IP69 protection, respectively, ideal for environments requiring more ruggedized or washdown components.

SWIR LED bar, backlight, and ringlight

Do you have an application you need tested with lights? Contact us and we can get your parts in the lab, test them and send images back.   If your materials can’t be shipped because they are spoilable foodstuffs, hazmat items, or such, contact us anyway and we’ll figure out how to source the items or bring lights to your facility.

Test and optimize lighting with customer materials

1st Vision’s sales engineers have over 100 years of combined experience to assist in your camera and components selection.  With a large portfolio of lensescablesNIC card and industrial computers, we can provide a full vision solution!

Components needed for machine vision and industrial imaging systems

Machine vision and industrial imaging systems are used in various applications ranging from automated quality control inspection, bottle filling, robot pick-and-place applications, autonomous drone or vehicle guidance, patient monitoring, agricultural irrigation controls, medical testing, metrology, and countless more applications.

Imaging systems typically include a least a camera and lens, and often also include one or more of specialized lighting, adapter cards, cables, software, optical filters, power supply, mount, or enclosure.

At 1stVision we’ve created a resource page is intended to make sure that nothing in a planned imaging application has been missed.  There are many aspects on which 1stVision can provide guidance.   The main components to consider are indicated below.

Diverse cameras

Cameras: There are area scan cameras for visible, infrared, and ultraviolet light, used for static or motion situations.  There are line scan cameras, often used for high-speed continuous web inspection.  Thermal imaging detects or measures heat.  SWIR cameras can identify the presence or even the characteristics of liquids.  The “best” camera depends on the part of the spectrum being sensed, together with considerations around motion, lighting, surface characteristics, etc.

An assortment of lens types and manufacturers

Lens: The lens focuses the light onto the sensor, mapping the targeted Field of View (FoV) from the real world onto the array of pixels.  One must consider image format to pair a suitable lens to the camera.  Lenses vary by the quality of their light-passing ability, how close to the target they can be – or how far from it, their weight (if on a robot arm it matters), vibration resistance,  etc.  See our resources on how to choose a machine vision lens.  Speak with us if you’d like assistance, or use the lens selector to browse for yourself.

Lighting: While ambient light is sufficient for some applications, specialized lighting may also be needed, to achieve sufficient contrast.  And it may not just be “white” light – Ultra-Violet (UV) or Infra-Red (IR) light, or other parts of the spectrum, sometimes work best to create contrast for a given application – or even to induce phosphorescence or scatter or some other helpful effect.  Additional lighting components may include strobe controllers or constant current drivers to provide adequate and consistent illumination. See also Lighting Techniques for Machine Vision.

Optical filter: There are many types of filters that can enhance application performance, or that are critical for success.  For example a “pass” filter only lets certain parts of the spectrum through, while a “block” filter excludes certain wavelengths.  Polarizing filters reduce glare.  And there are many more – for a conceptual overview see our blog on how machine filters create or enhance contrast

Don’t forget about interface adapters like frame grabbers and host adapters; cables; power supplies; tripod mounts; software; and enclosures. See the resource page to review all components one might need for an industrial imaging system, to be sure you haven’t forgotten anything.

1st Vision’s sales engineers have over 100 years of combined experience to assist in your camera and components selection.  With a large portfolio of lensescablesNIC card and industrial computers, we can provide a full vision solution!

How machine vision filters create contrast in machine vision applications

Before and after applying filters

Imaging outcomes depend crucially on contrast. It is only by making a feature “pop” relative to the larger image field in which the feature lies, that the feature can be optimally identified by machine vision software.

While sensor choice, lensing, and lighting are important aspects in building machine vision solutions with effective contrast creation, effective selection and application of filters can provide additional leverage for many applications. Often overlooked or misunderstood, here we provide a first-look at machine vision filter concepts and benefits.

Before and after applying filters

In the 4 image pairs above, each left-half image was generated with the same sensor, lighting, and exposure duration as the corresponding right-half images. But the right-half images have had filters applied to reduce glare or scratch-induced scatter, separate or block certain wavelengths, for example. If your brain finds the left-half images to be difficult to discern, image processing software wouldn’t be “happy” with the left-half either!

While there are also filtering benefits in color and SWIR imaging, it is worth noting that we started above with examples shown in monochrome. Surprising to many, it can often be both more effective and less expensive to create machine vision solutions in the monochrome space – often with filters – than in color. This may seem counter-intuitive, since most humans enjoy color vision, and use if effectively when driving, judging produce quality, choosing clothing that matches our skin tone, etc. But compared to using single-sensor color cameras, monochrome single sensor cameras paired with appropriate filters:

  • can offer higher contrast and better resolution
  • provide better signal-to-noise ratio
  • can be narrowed to sensitivity in near-ultraviolet, visible and near-infrared spectrums

These features give monochrome cameras a significant advantage when it comes to optical character recognition and verification, barcode reading, scratch or crack detection, wavelength separation and more. Depending on your application, monochrome cameras can be three times more efficient than color cameras.

Identify red vs. blue items

Color cameras may be the first thought when separating items by color, but it can be more efficient and effective to use a monochrome camera with a color bandpass filter. As shown above, to brighten or highlight an item that is predominantly red, using a red filter to transmit only the red portion of the spectrum can be used, blocking the rest of the transmitted light. The reverse can also work, using a blue filter to pass blue wavelengths while blocking red and other wavelengths.

Here we have touched on just a few examples, to whet the appetite. We anticipate developing a Tech Brief with a more in depth treatment of filters and their applications. We partner with Midwest Optical to offer you a wide range of filters for diverse application solutions.

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1st Vision’s sales engineers have an average of 20 years experience to assist in your camera selection.  Representing the largest portfolio of industry leading brands in imaging components, we can help you design the optimal vision solution for your application.

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